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Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to improve targeting and evaluation of responses to therapy in this disease are needed. Here, we integrate quantitative MRI data with biologically based mathematical modeling to accurately predict the response of TNBC to neoadjuvant systemic therapy (NAST) on an individual basis. Specifically, 56 patients with TNBC enrolled in the ARTEMIS trial (NCT02276443) underwent standard-of-care doxorubicin/cyclophosphamide (A/C) and then paclitaxel for NAST, where dynamic contrast-enhanced MRI and diffusion-weighted MRI were acquired before treatment and after two and four cycles of A/C. A biologically based model was established to characterize tumor cell movement, proliferation, and treatment-induced cell death. Two evaluation frameworks were investigated using: (i) images acquired before and after two cycles of A/C for calibration and predicting tumor status after A/C, and (ii) images acquired before, after two cycles, and after four cycles of A/C for calibration and predicting response following NAST. For Framework 1, the concordance correlation coefficients between the predicted and measured patient-specific, post-A/C changes in tumor cellularity and volume were 0.95 and 0.94, respectively. For Framework 2, the biologically based model achieved an area under the receiver operator characteristic curve of 0.89 (sensitivity/specificity = 0.72/0.95) for differentiating pathological complete response (pCR) from non-pCR, which is statistically superior (P < 0.05) to the value of 0.78 (sensitivity/specificity = 0.72/0.79) achieved by tumor volume measured after four cycles of A/C. Overall, this model successfully captured patient-specific, spatiotemporal dynamics of TNBC response to NAST, providing highly accurate predictions of NAST response. Significance: Integrating MRI data with biologically based mathematical modeling successfully predicts breast cancer response to chemotherapy, suggesting digital twins could facilitate a paradigm shift from simply assessing response to predicting and optimizing therapeutic efficacy.

This study aimed to investigate mid-treatment breast tumor ultrasound characteristics that may predict eventual pathologic complete response (pCR) in triple-negative breast cancer; specifically, we examined associations between pCR and two parameters: tumor response pattern and tumor appearance. Ultrasound was performed at mid-treatment, defined as the completion of four cycles of anthracycline-based chemotherapy and before receiving taxane-based chemotherapy. Consensus imaging review was performed while blinded to pathology results (i.e., pCR/non-pCR) from surgery. Tumor response pattern was described as "complete," "concentric," "fragmented," "stable" or "progression." Tumor appearance was designated as "mass," "architectural distortion," "flat tumor bed" or "clip only." Univariate and multivariate regression analyses of 144 participants showed significant associations between mid-treatment response pattern and pCR (p = 0.0348 and p = 0.0173, respectively), with complete and concentric response patterns more likely to achieve pCR than other patterns. Univariate and multivariate regression analyses further showed significant associations between mid-treatment tumor appearance and pCR (p0.0001 for both), with persistent appearance of mass less likely than other appearances to achieve pCR. To conclude, our study demonstrated strong associations between pCR and both tumor response pattern and tumor appearance, thereby suggesting that these parameters have potential as qualitative imaging biomarkers of pCR in triple-negative breast cancer.

Background and Purpose: There is currently lack of recognized imaging criteria for prediction of treatment response to NAST in breast cancer patients. And early identification of treatment response to neoadjuvant systemic therapy (NAST) in Triple Negative Breast Cancer (TNBC) patients is important for appropriate treatment selection and response monitoring. A novel MRI sequence, Magnetic Resonance Image Compilation (MagIC) is capable of simultaneous quantitation of several tissue water properties including longitudinal (T1), transverse (T2) relaxation times, and proton density (PD). In this study we evaluated the ability of a radiomic model extracted from a novel MagIC sequence acquired early during NAST to predict pathologic complete response to NAST in TNBC. Materials and Methods: This IRB approved prospective ARTEMIS trial (NCT02276443) included 184 women (122 training dataset, 62 testing dataset) diagnosed with stage I-III TNBC. All patients were scanned with MagIC on a 3T MRI scanner at baseline (184 patients), and after 4 cycles (156 Patients) of NAST. T1, T2 and PD maps were generated from the source images using SyMRI (SyntheticMR, Linkoping, Sweden). Histopathology at surgery was used to determine pathologic complete response (pCR) which was defined as absence of the invasive cancer in the breast and axillary lymph nodes. 3D contouring of the tumors was performed using an in-house toolbox. 310 (10 first-order, 300 GLCM) textural features were extracted from each map, with total of 930 features/patient. Radiomic features were compared between pCR and non-pCR using Wilcoxon Rank Sum test and Fisher’s exact test. To build a multivariate, predictive model, logistic regression with elastic net regularization was performed for texture feature selection. The tuning parameter was optimized using 5-fold cross-validation based on the average area under curve (AUC) of each fold of a cross-validation using training data. Then the testing data were used to compare model’s performance by AUC. Results: Univariate analysis found 23 PD, 17 T1 and 10 T2 radiomic features at C4 time point to be able to predict pCR status with AUC >70% in both training and testing cohort. The top performing radiomic features were Entropy, Variance, Homogeneity and Energy (Tables1-2). Multivariate radiomics models from C4-PD, and C4-T1 maps showed best performance during both cross validation and independent testing. The radiomic signature of C4-T1 map that included 27features had best performance, with an AUC of 0.77, 0.70 (95% CI: 0.571-0.868) in training and testing cohort respectively. C4-PD map radiomic signature that included 6features was able to predict the pCR status with AUC of 0.73, 0.72 (95% CI: 0.571-0.868) in training and testing cohort respectively. Conclusion: Our data found that MagIC-based radiomics signature could potentially predict pathologic complete response in TNBC early during NAST. This data shows the potential application of MagIC radiomic model for improvement of response assessment in TNBC. Table 1.Best performing radiomic features from PD map after 4 cycles of NAST in TNBC patients.FeatureTraining CohortTraining CohortTraining CohortTesting CohortTesting CohortTesting CohortNAUC95% CINAUC95% CIP-valuePD-mapAngular Variance of Sum entropy1060.73820.6437-0.8328500.73240.5895-0.8752 Table 2.Best performing radiomic features from T1-T2 maps after 4 cycles of NAST in TNBC patients.FeatureTraining CohortTraining CohortTraining CohortTesting CohortTesting CohortTesting CohortNAUC95% CINAUC95% CIP-valueT1-mapAngular Variance of Sum entropy1060.76530.6762-0.8544500.70510.5524-0.8579 Citation Format: Nabil Elshafeey, Ken-Pin Hwang, Beatriz Elena Adrada, Rosalind Pitpitan Candelaria, Medine Boge, Rania M Mahmoud, Huiqin Chen, Jia Sun, Wei Yang, Aikaterini Kotrotsou, Benjamin C Musall, Jong Bum Son, Gary J Whitman, Jessica Leung, Huong Le-Petross, Lumarie Santiago, Deanna Lynn Lane, Marion Elizabeth Scoggins, David Allen Spak, Mary Saber Guirguis, Miral Mahesh Patel, Frances Perez, Abeer H Abdelhafez, Jason B White, Lei Huo, Elizabeth Ravenberg, Wei Peng, Alastair Thompson, Senthil Damodaran, Debu Tripathy, Stacey L Moulder, Clinton Yam, Mark David Pagel, Jingfei Ma, Gaiane Margishvili Rauch. Radiomics model based on magnetic resonance image compilation (MagIC) as early predictor of pathologic complete response to neoadjuvant systemic therapy in triple-negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD11-06.

Background: TNBC constitutes an aggressive and heterogeneous group of tumors with variable response to neoadjuvant therapy (NAT) that currently lacks clinically available profiling strategies for prediction. We aimed to develop an integrated model based on imaging, pathological and clinical data capable to predict NAT response in TNBC early during therapy. METHOD AND MATERIALS:125 Stage I-III TNBC patients enrolled in an IRB approved prospective clinical trial (NCT02276433) who had DCE-MRI at baseline (BL) and post 2 cycles (C2) of NAT, and had surgery were included in this analysis. Tumor volume was calculated using 3D measurements at BL and C2 time points DCE-MRI. Percent tumor volume reduction (TVR) between BL and C2 was calculated. Demographic, clinical, and pathological data (age, T and N stage, histology, androgen receptor expression, Ki-67, stromal tumor infiltrating lymphocytes level (sTIL), and PD-L1 expression), and treatment response at surgery (pCR vs non-pCR) were documented. Recursive partitioning was used to identify TVR cutoff value. Multivariate logistic regression and ROC analysis were used to assess associations and build and evaluate predictive models. RESULTS: 61 (49%) TNBC pts showed pCR at surgery, and 64 (51%) non-pCR. Recursive partitioning analysis identified ≥ 55% TVR as the optimal cutoff values for pCR prediction at C2. TVR, N stage and sTIL were significantly associated with pCR in the multivariate analyses (p Citation Format: Gaiane Margishvili Rauch, Rosalind P. Candelaria, Mary Saber Guirguis, Medine Boge, Rania M. M. Mohamed, Nabil Elshafeey, Jia Sun, Gary J Whitman, Jessica Leung, Huong C Le-Petross, Lumarie Santiago, Deanna Lane, Marion Scoggins, David Spak, Miral M Patel, Frances Perez, Jason B. White, Elizabeth Ravenberg, Wei Peng, Debu Tripathy, Vicente Valero, Jennifer Litton, Lei Huo, Clinton Yam, Alastair Thompson, Jingfei Ma, Stacy L. Moulder, Wei Yang, Beatriz E. Adrada. Integrated model for early prediction of neoadjuvant systemic therapy response in triple negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD11-07.

Introduction: Neoadjuvant chemotherapy (NACT) is becoming standard of care for presurgical treatment of triple negative breast cancer (TNBC) patients. Achievement of pathological complete response (pCR) after NACT is associated with improved outcomes. There is currently an unmet need in development of imaging and clinical tools for prediction of pCR to NACT in TNBC. We investigated use of deep learning convolution neural networks (CNNs) for early prediction of pCR in a TNBC cohort on the basis of MRI acquired before the initiation and at the midpoint, after completion of four cycles of NACT (C4). Materials and Methods: Baseline and C4 MRIs of 112 TNBC patients were collected from an ongoing prospective clinical trial (NCT02276443). Four patients were excluded because they underwent different treatment for the second regimen. Among the 108 patients, 52 patients (48%) had pCR confirmed at surgery. Positive enhancement integral (PEI) derived from the early phases of DCE MRI, and apparent diffusion coefficients (ADC) derived from DWI MRI (b = 100 and 800 s/mm2), were used for our investigation. The images were aligned and the tumor regions were cropped from all images. All tumor patches were normalized between [0, 1], and were padded to form matrices of the same size of 192×192×64 for PEI, or the size of 192×192×16 for ADC. The CNN was constructed using stacked 3D convolution and MaxPooling layers. It consisted of up to four channels for the inputs (baseline and C4 PEI and ADC). Features extracted from each channel were concatenated and regressed for pCR prediction via three densely connected layers. Binary cross-entropy was used as the loss function for CNN training, and the loss was optimized using an Adam optimizer with the initial learning rate of 0.0001. Because of the currently limited sample size, four-fold cross-validation was used for CNN training and evaluation. The patients were divided into four groups, each group had 27 patients and the pCR:non-pCR ratio was controlled as 13:14. For each fold, one group was reserved as the independent testing group, and the other three groups were combined for network training and internal validation. Receiver operating characteristic (ROC) curve was plotted for each fold of testing, and area under the curve (AUC) was calculated. Final performance of the CNN was determined by averaging the AUCs of the four testing folds. Additionally, to test the prediction efficacy of each input, we trained the CNN under the same settings but used PEI or ADC only as input, and the results were compared. Results: The CNN trained with PEI only achieved an average AUC of 0.65 ± 0.09. The second CNN trained with ADC only achieved an average AUC of 0.72 ± 0.07. The third CNN trained with both PEI and ADC achieved an average AUC of 0.73 ± 0.06. Conclusion and Discussion: Using baseline and mid-treatment MRIs, deep learning CNN showed promising performance to predict pCR in the early course of NACT. The prediction AUC for the independent testing groups was largely improved by using ADC to train the network, indicating that ADC can have more critical information than PEI in assisting pCR prediction during the early course of NACT. Future work includes curation of a larger patient data for network training and evaluation to improve the prediction performance and further validate generalization of the network. We will also explore more advanced network structures, through which the prediction performance can be improved. Four-fold cross-validation AUCs of the network using different data as inputs.PEIADCPEI+ADCFold 10.570.640.66Fold 20.760.800.77Fold 30.660.700.68Fold 40.590.740.79Average0.65 ± 0.090.72 ± 0.070.73 ± 0.06 Citation Format: Zijian Zhou, Nabil A Elshafeey, David E Rauch, Beatriz E Adrada, Rosalind P Candelaria, Mary S Guirguis, Wei Yang, Medine Boge, Rania M Mohamed, Gary J Whitman, Deanna L Lane, Huong C Le-Petross, Jessica WT Leung, Lumarie Santiago, Marion E Scoggins, David A Spak, Miral M Patel, Frances Perez, Debu Tripathy, Vicente Valero, Clinton Yam, Stacy Moulder, Jason B White, Jong Bum Son, Mark D Pagel, Jingfei Ma. Deep learning for early prediction of neoadjuvant chemotherapy response in triple negative breast cancers [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-03.

Supplementary Tables S1-5 and Supplementary Fig. S1

Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to improve targeting and evaluation of responses to therapy in this disease are needed. Here, we integrate quantitative MRI data with biologically based mathematical modeling to accurately predict the response of TNBC to neoadjuvant systemic therapy (NAST) on an individual basis. Specifically, 56 patients with TNBC enrolled in the ARTEMIS trial (NCT02276443) underwent standard-of-care doxorubicin/cyclophosphamide (A/C) and then paclitaxel for NAST, where dynamic contrast-enhanced MRI and diffusion-weighted MRI were acquired before treatment and after two and four cycles of A/C. A biologically based model was established to characterize tumor cell movement, proliferation, and treatment-induced cell death. Two evaluation frameworks were investigated using: (i) images acquired before and after two cycles of A/C for calibration and predicting tumor status after A/C, and (ii) images acquired before, after two cycles, and after four cycles of A/C for calibration and predicting response following NAST. For Framework 1, the concordance correlation coefficients between the predicted and measured patient-specific, post-A/C changes in tumor cellularity and volume were 0.95 and 0.94, respectively. For Framework 2, the biologically based model achieved an area under the receiver operator characteristic curve of 0.89 (sensitivity/specificity = 0.72/0.95) for differentiating pathological complete response (pCR) from non-pCR, which is statistically superior (P < 0.05) to the value of 0.78 (sensitivity/specificity = 0.72/0.79) achieved by tumor volume measured after four cycles of A/C. Overall, this model successfully captured patient-specific, spatiotemporal dynamics of TNBC response to NAST, providing highly accurate predictions of NAST response.Significance:Integrating MRI data with biologically based mathematical modeling successfully predicts breast cancer response to chemotherapy, suggesting digital twins could facilitate a paradigm shift from simply assessing response to predicting and optimizing therapeutic efficacy.

Supplementary Figure from Molecular Characterization and Prospective Evaluation of Pathologic Response and Outcomes with Neoadjuvant Therapy in Metaplastic Triple-Negative Breast Cancer

Supplementary Data from MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Purpose:Metaplastic breast cancer (MpBC) is a rare subtype of breast cancer that is commonly triple-negative and poorly responsive to neoadjuvant therapy in retrospective studies.Experimental Design:To better define clinical outcomes and correlates of response, we analyzed the rate of pathologic complete response (pCR) to neoadjuvant therapy, survival outcomes, and genomic and transcriptomic profiles of the pretreatment tumors in a prospective clinical trial (NCT02276443). A total of 211 patients with triple-negative breast cancer (TNBC), including 39 with MpBC, received doxorubicin-cyclophosphamide–based neoadjuvant therapy.Results:Although not meeting the threshold for statistical significance, patients with MpBCs were less likely to experience a pCR (23% vs. 40%; P = 0.07), had shorter event-free survival (29.4 vs. 32.2 months, P = 0.15), metastasis-free survival (30.3 vs. 32.4 months, P = 0.22); and overall survival (32.6 vs. 34.3 months, P = 0.21). This heterogeneity is mirrored in the molecular profiling. Mutations in PI3KCA (23% vs. 9%, P = 0.07) and its pathway (41% vs. 18%, P = 0.02) were frequently observed and enriched in MpBCs. The gene expression profiles of each histologically defined subtype were distinguishable and characterized by distinctive gene signatures. Among nonmetaplastic (non-Mp) TNBCs, 10% possessed a metaplastic-like gene expression signature and had pCR rates and survival outcomes similar to MpBC.Conclusions:Further investigations will determine if metaplastic-like tumors should be treated more similarly to MpBC in the clinic. The 23% pCR rate in this study suggests that patients with MpBC should be considered for NAT. To improve this rate, a pathway analysis predicted enrichment of histone deacetylase (HDAC) and RTK/MAPK pathways in MpBC, which may serve as new targetable vulnerabilities.

Purpose:Increasing tumor-infiltrating lymphocytes (TIL) is associated with higher rates of pathologic complete response (pCR) to neoadjuvant therapy (NAT) in patients with triple-negative breast cancer (TNBC). However, the presence of TILs does not consistently predict pCR, therefore, the current study was undertaken to more fully characterize the immune cell response and its association with pCR.Experimental Design:We obtained pretreatment core-needle biopsies from 105 patients with stage I–III TNBC enrolled in ARTEMIS (NCT02276443) who received NAT from Oct 22, 2015 through July 24, 2018. The tumor-immune microenvironment was comprehensively profiled by performing T-cell receptor (TCR) sequencing, programmed death-ligand 1 (PD-L1) IHC, multiplex immunofluorescence, and RNA sequencing on pretreatment tumor samples. The primary endpoint was pathologic response to NAT.Results:The pCR rate was 40% (42/105). Higher TCR clonality (median = 0.2 vs. 0.1, P = 0.03), PD-L1 positivity (OR: 2.91, P = 0.020), higher CD3+:CD68+ ratio (median = 14.70 vs. 8.20, P = 0.0128), and closer spatial proximity of T cells to tumor cells (median = 19.26 vs. 21.94 μm, P = 0.0169) were associated with pCR. In a multivariable model, closer spatial proximity of T cells to tumor cells and PD-L1 expression enhanced prediction of pCR when considered in conjunction with clinical stage.Conclusions:In patients receiving NAT for TNBC, deep immune profiling through detailed phenotypic characterization and spatial analysis can improve prediction of pCR in patients receiving NAT for TNBC when considered with traditional clinical parameters.

Supplementary Table from Molecular Characterization and Prospective Evaluation of Pathologic Response and Outcomes with Neoadjuvant Therapy in Metaplastic Triple-Negative Breast Cancer

Purpose: Increasing tumor-infiltrating lymphocytes (TIL) is associated with higher rates of pathologic complete response (pCR) to neoadjuvant therapy (NAT) in patients with triple-negative breast cancer (TNBC). However, the presence of TILs does not consistently predict pCR, therefore, the current study was undertaken to more fully characterize the immune cell response and its association with pCR. Experimental Design: We obtained pretreatment core-needle biopsies from 105 patients with stage I–III TNBC enrolled in ARTEMIS (NCT02276443) who received NAT from Oct 22, 2015 through July 24, 2018. The tumor-immune microenvironment was comprehensively profiled by performing T-cell receptor (TCR) sequencing, programmed death-ligand 1 (PD-L1) IHC, multiplex immunofluorescence, and RNA sequencing on pretreatment tumor samples. The primary endpoint was pathologic response to NAT. Results: The pCR rate was 40% (42/105). Higher TCR clonality (median = 0.2 vs. 0.1, P = 0.03), PD-L1 positivity (OR: 2.91, P = 0.020), higher CD3+:CD68+ ratio (median = 14.70 vs. 8.20, P = 0.0128), and closer spatial proximity of T cells to tumor cells (median = 19.26 vs. 21.94 μm, P = 0.0169) were associated with pCR. In a multivariable model, closer spatial proximity of T cells to tumor cells and PD-L1 expression enhanced prediction of pCR when considered in conjunction with clinical stage. Conclusions: In patients receiving NAT for TNBC, deep immune profiling through detailed phenotypic characterization and spatial analysis can improve prediction of pCR in patients receiving NAT for TNBC when considered with traditional clinical parameters.

BACKGROUND Heterogeneity exists in the response of triple-negative breast cancer (TNBC) to standard anthracycline (AC)/taxane-based neoadjuvant systemic therapy (NAST), with 40% to 50% of patients having a pathologic complete response (pCR) to therapy. Early assessment of the imaging response during NAST may identify a subset of TNBCs that are likely to have a pCR upon completion of treatment. The authors aimed to evaluate the performance of early ultrasound (US) after 2 cycles of neoadjuvant NAST in identifying excellent responders to NAST among patients with TNBC. METHODS Two hundred fifteen patients with TNBC were enrolled in the ongoing ARTEMIS (A Robust TNBC Evaluation Framework to Improve Survival) clinical trial. The patients were divided into a discovery cohort (n = 107) and a validation cohort (n = 108). A receiver operating characteristic analysis with 95% confidence intervals (CIs) and a multivariate logistic regression analysis were performed to model the probability of a pCR on the basis of the tumor volume reduction (TVR) percentage by US from the baseline to after 2 cycles of AC. RESULTS Overall, 39.3% of the patients (42 of 107) achieved a pCR. A positive predictive value (PPV) analysis identified a cutoff point of 80% TVR after 2 cycles; the pCR rate was 77% (17 of 22) in patients with a TVR ≥ 80%, and the area under the curve (AUC) was 0.84 (95% CI, 0.77-0.92; P < .0001). In the validation cohort, the pCR rate was 44%. The PPV for pCR with a TVR ≥ 80% after 2 cycles was 76% (95% CI, 55%-91%), and the AUC was 0.79 (95% CI, 0.70-0.87; P < .0001). CONCLUSIONS The TVR percentage by US evaluation after 2 cycles of NAST may be a cost-effective early imaging biomarker for a pCR to AC/taxane-based NAST.

Fields, JB, Lameira, DM, Short, JL, Merrigan, JM, Gallo, S, White, JB, and Jones, MT. Relationship between external load and self-reported wellness measures across a collegiate men's soccer preseason. J Strength Cond Res 35(5): 1182-1186, 2021-Monitoring athlete training load is important to training programming and can help balance training and recovery periods. Furthermore, psychological factors can affect athlete's performance. Therefore, the purpose was to examine the relationship between external load and self-reported wellness measures during soccer preseason. Collegiate men soccer athletes (n = 20; mean ± SD age: 20.3 ± 0.9 years; body mass: 77.9 ± 6.8 kg; body height: 178.87 ± 7.18cm; body fat: 10.0 ± 5.0%; Vo2max: 65.39 ± 7.61ml·kg-1·min-1) participated. Likert scale self-assessments of fatigue, soreness, sleep, stress, and energy were collected daily in conjunction with the Brief Assessment of Mood (vigor, depression, anger, fatigue, and confusion). Total distance (TD), player load (PL), high-speed distance (HSD, >13 mph [5.8 m·s-1]), high inertial movement analysis (IMA, >3.5 m·s-2), and repeated high-intensity efforts (RHIEs) were collected in each training session using positional monitoring (global positioning system/global navigation satellite system [GPS/GNSS]) technology. Session rate of perceived exertion (sRPE) was determined from athlete's post-training rating (Borg CR-10 Scale) and time of training session. Multilevel models revealed the bidirectional prediction of load markers on fatigue, soreness, sleep, energy, and sRPE (p < 0.05). Morning ratings of soreness and fatigue were predicted by previous afternoon's practice measures of TD, PL, HSD, IMA, RHIE, and sRPE. Morning soreness and fatigue negatively predicted that day's afternoon practice TD, PL, HSD, IMA, RHIE, and sRPE. Morning ratings of negative mood were positively predicted by previous day's afternoon practice HSD. In addition, negative morning mood states inversely predicted HSD (p = 0.011), TD (p = 0.002), and PL (p < 0.001) for that day's afternoon practice. Using self-reported wellness measures with GPS/GNSS technology may enhance the understanding of training responses and inform program development.

Background: Triple negative breast cancer (TNBC) disproportionally impacts Black and Hispanic women and is suggested to be partly responsible for disparities observed in breast cancer mortality. We sought to evaluate the impact of race/ethnicity on TNBC molecular subtype, immune profile, pathologic complete response (pCR) and recurrence free survival (RFS). Methods: The ARTEMIS trial (NCT02276443) uses imaging response and molecular profiling to personalize neoadjuvant chemotherapy in early stage TNBC. After 4 cycles of AC, patients with chemo-sensitive disease receive standard taxane-based therapy, while those with chemo-resistant disease are offered therapeutic trials based upon molecular profiling. Pathologic response was assessed at surgery. Patients self-reported race/ethnicity was categorized as Asian, Black/African-American, Hispanic/Latino and White (non-Hispanic). Patients were excluded if no race or ethnicity was reported. Clinical and pathologic factors were recorded and compared. Gene expression profiling was performed by RNAseq to determine Vanderbilt signature. PD-L1 and Androgen Receptor (AR) were determined by immunohistochemistry. Frequencies at which various factors were observed by race/ethnicity were calculated and Fisher’s exact test performed to determine statistical significance. Kaplan-Meier analysis was used to estimate survival stratified by pCR status and race/ethnicity. Results: Among 321 women enrolled in ARTEMIS, 26 (8.1%) were classified as Asian, 50 (15.6%) as Black, 59 (18.4%) as Hispanic and 186 (57.9%) as White. Demographic and clinical features were similar, except Black women were more likely to have BMI ≥30 (70.0%, p Conclusion: Among this population of patients with TNBC treated with neoadjuvant chemotherapy there was no statistically significant difference observed in TNBC Vanderbilt signature, PD-L1 staining, sTIL, pCR or RFS by race/ethnicity. Asian women were found to have a higher incidence of AR-positive subtype. Numerically higher rates of N3 stage in Black women and RCB-III classification in Black and Hispanic women were identified, however not statistically significant. Larger cohorts of patients are needed to further investigate these findings. Table 1. TNBC profiling compared by race/ethnicity.Total n (%)Asian n (%)Black n (%)Hispanic/Latino n (%)White n (%)p valueVanderbilt signature n (%) Basal like (BL1) Basal like 2 (BL2) Immunomodulatory (IM) Luminal androgen receptor (LAR) Mesenchymal (M) Mesenchymal stem-like (MSL) Unstable (UNS)231 50 (21.6) 25 (10.8) 42 (18.2) 22 (9.5) 48 (20.8) 14 (6.0) 30 (13.0)21 (9.1) 0 (0.0) 4 (19.0) 5 (23.8) 3 (14.3) 5 (23.8) 1 (4.8) 3 (14.3)35 (15.2) 9 (25.7) 5 (14.3) 6 (17.1) 2 (5.7) 7 (20.0) 1 (2.9) 5 (14.3)43 (18.6) 14 (32.5) 3 (7.0) 10 (23.2) 5 (11.6) 6 (14.0) 2 (4.7) 3 (7.0)132 (57.1) 27 (20.5) 13 (9.8) 21 (15.9) 12 (9.1) 30 (22.7) 10 (7.6) 19 (14.4)NSAndrogen Receptor n (%) Positive (>=10%) Negative (1298 212 (71.1) 86 (28.9)24 (8.1) 15 (62.5) 9 (37.5)47 (15.8) 33 (70.2) 14 (29.8)57 (19.1) 40 (70.2) 17 (29.8)170 (57.0) 124 (72.9) 46 (27.1)NSStromal tumor infiltrating lymphocytes (sTIL) n (%) High (>=20%) Low ( Citation Format: Mediget Teshome, Ryan Sun, Elizabeth E. Ravenberg, Abenaa Brewster, Mariana Chavez-MacGregor, Jason B. White, Stacy Moulder. Impact of race/ethnicity on triple negative breast cancer molecular features, treatment response and clinical outcomes in patients receiving neoadjuvant therapy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-12.

Introduction CEST MRI permits quantitation of macromolecules such as amide proteins that are of interest in cancer metabolism. However, optimal CEST acquisition and analysis methods remain undetermined. In this study, we investigated CEST MRI as an imaging biomarker for early treatment response in 51 TNBC patients receiving NAST and compared the performance with two different CEST saturation power levels and two analysis methods. Methods A total of 51 stage I-III TNBC patients enrolled in the prospective ARTEMIS trial (NCT02276443) had CEST imaging performed on a 3T MRI scanner at baseline before NAST (BL, N = 51), after 2 cycles (C2, N = 37), and 4 cycles (C4, N = 44) of NAST. 33 of the 51 patients had imaging at all 3 time points. 29 of the 33 patients had pathological findings, with N = 16 with pathological complete response (pCR) and N = 13 with non-pCR. Two sets of CEST images using 0.9 and 2.0 µT saturation power levels were acquired and analyzed using the magnetization transfer ratio asymmetry (MTRasym) and the Lorentzian line fitting (Mag3.5) methods, for a total of 4 acquisition/analysis combinations. The group averaged CEST signals, MTRasym at 0.9 and 2.0 µT and Mag3.5 at 0.9 and 2.0 µT, at BL, C2 and C4 were determined and evaluated using unpaired (51 patients) and paired (33 patients) Kruskal-Wallis tests. The Mag3.5 at 0.9 µT and the MTRasym at 2.0 µT were further compared between pCR and non-pCR. The group averaged CEST signals at BL, C2, and C4 were evaluated using the Friedman test for the pCR and the non-PCR groups. Separately, the change in the CEST signal from BL to C2 and C4 was determined for each patient and evaluated using the Mann-Whitney test for both groups. P < 0.05 was considered statistically significant. Results The MTRasym at BL was higher at 2.0 µT than at 0.9 µT. In contrast, the Mag3.5 at BL was higher at 0.9 µT than at 2.0 µT. The MTRasym at 2.0 µT and the Mag3.5 at 0.9 µT decreased during treatment while the MTRasym at 0.9 µT and the Mag3.5 at 2.0 µT were similar. Both the unpaired and the paired Mag3.5 at 0.9 µT showed a significant decrease at C2 and C4 vs. BL (p < 0.01). The unpaired and paired MTRasym at 2.0 µT showed a decrease, although the change was not significant except for the unpaired data at C4. The decrease in the group averaged Mag3.5 at 0.9 µT was significant at C2 vs. BL for the pCR group (p = 0.04), while it was not significant for the pCR group at C4 vs. BL and for the non-pCR group at either C2 or C4 vs. BL. The group averaged MTRasym at 2.0 µT changes were not significant for either the pCR or the non-pCR groups. None of the CEST signal changes on a per patient basis at C2-BL, C4-BL and C4-C2 were significantly different between the pCR and the non-pCR groups. Further, none of the group averaged CEST signals at BL, C2 and C4 were significantly different between the pCR and the non-pCR groups. Conclusion Our study demonstrates that the CEST quantitation in TNBC patients undergoing NAST depends on acquisition and analysis. For a maximum change in the CEST effect, Lorentzian line fitting is better paired with acquisition at a low saturation power (0.9 µT) and MTRasym is better paired with acquisition at a high saturation power (2.0 µT). Further, a significant CEST signal decrease was observed in TNBC patients with pCR after NAST when a 0.9 µT saturation power and the Lorentzian line fitting were used. In comparison, the decrease was not significant in non-pCR patients using the same saturation power and analysis method. The results suggest that the CEST signal acquired at 0.9 µT saturation power and analyzed using Lorentzian line fitting may be able to differentiate between pCR and non-pCR among TNBC patients undergoing NAST. Additional studies with a larger patient population are ongoing to further validate our findings and their potential for determining pCR. Citation Format: Shu Zhang, Gaiane M Rauch, Beatriz E Adrada, Medine Boge, Rania MM Mohamed, Abeer H Abdelhafez, Jong Bum Son, Jia Sun, Nabil A Elshafeey, Jason B White, Deanna L Lane, Jessica WT Leung, Marion E Scoggins, David A Spak, Elsa Arribas, Elizabeth Ravenberg, Lumarie Santiago, Tanya W Moseley, Gary J Whitman, Huong Le-Petross, Benjamin C Musall, Mitsuharu Miyoshi, Xinzeng Wang, Brandy Willis, Stacy Hash, Aikaterini Kotrotsou, Peng Wei, Ken-Pin Hwang, Alastair Thompson, Stacy L Moulder, Rosalind P Candelaria, Wei Yang, Jingfei Ma, Mark D Pagel. Assessment of early response to neoadjuvant systemic therapy (NAST) of triple-negative breast cancer (TNBC) using chemical exchange saturation transfer (CEST) MRI: A pilot study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-08.

Purpose:Metaplastic breast cancer (MpBC) is a rare subtype of breast cancer that is commonly triple-negative and poorly responsive to neoadjuvant therapy in retrospective studies.Experimental Design:To better define clinical outcomes and correlates of response, we analyzed the rate of pathologic complete response (pCR) to neoadjuvant therapy, survival outcomes, and genomic and transcriptomic profiles of the pretreatment tumors in a prospective clinical trial (NCT02276443). A total of 211 patients with triple-negative breast cancer (TNBC), including 39 with MpBC, received doxorubicin-cyclophosphamide–based neoadjuvant therapy.Results:Although not meeting the threshold for statistical significance, patients with MpBCs were less likely to experience a pCR (23% vs. 40%; P = 0.07), had shorter event-free survival (29.4 vs. 32.2 months, P = 0.15), metastasis-free survival (30.3 vs. 32.4 months, P = 0.22); and overall survival (32.6 vs. 34.3 months, P = 0.21). This heterogeneity is mirrored in the molecular profiling. Mutations in PI3KCA (23% vs. 9%, P = 0.07) and its pathway (41% vs. 18%, P = 0.02) were frequently observed and enriched in MpBCs. The gene expression profiles of each histologically defined subtype were distinguishable and characterized by distinctive gene signatures. Among nonmetaplastic (non-Mp) TNBCs, 10% possessed a metaplastic-like gene expression signature and had pCR rates and survival outcomes similar to MpBC.Conclusions:Further investigations will determine if metaplastic-like tumors should be treated more similarly to MpBC in the clinic. The 23% pCR rate in this study suggests that patients with MpBC should be considered for NAT. To improve this rate, a pathway analysis predicted enrichment of histone deacetylase (HDAC) and RTK/MAPK pathways in MpBC, which may serve as new targetable vulnerabilities.

Folate receptor alpha (FRα) has been reported to be expressed in up to 80% of triple-negative breast cancers (TNBC) with limited expression in normal tissues, making it a promising therapeutic target. Mirvetuximab soravtansine (mirvetuximab-s) is an antibody drug conjugate which has shown promise in the treatment of FRα-positive solid tumors in early phase clinical trials. Herein, are the results of the first prospective phase II trial evaluating mirvetuximab-s in metastatic TNBC. Patients with advanced, FRα-positive TNBC were enrolled on this study. Mirvetuximab-s was administered at a dose of 6.0 mg/kg every 3 weeks. 96 patients with advanced TNBC consented for screening. FRα staining was performed on tumor tissue obtained from 80 patients. The rate of FRα positivity by immunohistochemistry was 10.0% (8/80). Two patients were treated on study, with best overall responses of stable disease in one and progressive disease in the other. Adverse events were consistent with earlier studies. The study was terminated early due to the low rate of FRα positivity in the screened patient population and lack of disease response in the two patients treated. The observed rate of FRα positivity was considerably lower than previously reported and none of the patients had a partial or complete response. Treatment with mirvetuximab-s should only be further explored in TNBC if an alternate biomarker strategy is developed for patient selection on the basis of additional preclinical data.

PURPOSE: To determine if tumor necrosis by pretreatment breast MRI and its quantitative imaging characteristics are associated with response to NAST in TNBC. METHODS: This retrospective study included 85 TNBC patients (mean age 51.8 ± 13 years) with MRI before NAST and definitive surgery during 2010–2018. Each MRI included T2-weighted, diffusion-weighted (DWI), and dynamic contrast-enhanced (DCE) imaging. For each index carcinoma, total tumor volume including necrosis (TTV), excluding necrosis (TV), and the necrosis-only volume (NV) were segmented on early-phase DCE subtractions and DWI images. NV and %NV were calculated. Percent enhancement on early and late phases of DCE and apparent diffusion coefficient were extracted from TTV, TV, and NV. Association between necrosis with pathological complete response (pCR) was assessed using odds ratio (OR). Multivariable analysis was used to evaluate the prognostic value of necrosis with T stage and nodal status at staging. Mann–Whitney U tests and area under the curve (AUC) were used to assess performance of imaging metrics for discriminating pCR vs non-pCR. RESULTS: Of 39 patients (46%) with necrosis, 17 had pCR and 22 did not. Necrosis was not associated with pCR (OR, 0.995; 95% confidence interval [CI] 0.4–2.3) and was not an independent prognostic factor when combined with T stage and nodal status at staging (P = 0.46). None of the imaging metrics differed significantly between pCR and non-pCR in patients with necrosis (AUC < 0.6 and P > 0.40). CONCLUSION: No significant association was found between necrosis by pretreatment MRI or the quantitative imaging characteristics of tumor necrosis and response to NAST in TNBC.

Background:While TNBC patients with pathologic complete response (pCR) or residual cancer burden (RCB-I) have good survival rates, those with extensive residual disease (RCB-II or RCB-III) after neoadjuvant chemotherapy (NACT) have poor prognosis. Patients without response to their first chemotherapeutic regimen have very low chance (5%) of achieving pCR. We have created a biomarker-driven drug development strategy, ARTEMIS (A Randomized, TNBC Enrolling trial to confirm Molecular profiling Improves Survival) to identify novel targeted therapies focusing on chemo-insensitive disease. The PI3K/Akt/mTOR pathway is a critical regulator of cell growth, apoptosis, metabolism in cancer cells and its activation is known to play an important role in resistance to chemotherapy. Clinical studies have shown that the combination of PI3K pathway inhibitors with taxanes are associated with improvement in response rates and survival. Alpelisib is approved for hormone receptor positive, HER2 negative, metastatic breast cancer patients with activating PIK3CA mutations. This study hypothesizes combination of alpelisib with nab-paclitaxel will improve PCR/RCB-1 in treatment-resistant early stage TNBC patients with activating PIK3CA or PTEN loss of function alterations. Trial Design: This will be a non-randomized, two- arm, open label, phase II study to evaluate the clinical activity of alpelisib and nab-paclitaxel in high-risk TNBC patients with PIK3CA or PTEN alterations with refractory or suboptimal response to anthracycline-based NACT. Eligibility criteria Stage 1-3 TNBC defined as ER Specific aims To determine if alpelisib in combination with nab-paclitaxel will improve rates of pathologic response (pCR/RCB-0 or RCB-I) from 5% to 20% in patients with chemotherapy insensitive TNBC with activating PIK3CA alterations (Arm-1) or PTEN loss of function alterations (Arm-2)To determine the radiographic response rate for alpelisib in combination with nab-paclitaxel in chemotherapy insensitive TNBC with PIK3CA (Arm-1) or PTEN (Arm-2) alterationsDetermine toxicity of alpelisib in combination with nab-paclitaxel given in the neoadjuvant settingDetermine progression free survival (PFS) at 3 years for patients treated with alpelisib in combination with nab-paclitaxel given in the neoadjuvant setting Statistical methods Primary objective is to determine if alpelisib in combination with nab-paclitaxel in the neoadjuvant setting will improve rates of pathologic response (counting pCR/RCB-0 or RCB-I as response) from 5% (control) to 20% (experimental arms). A Simon two-stage design will be employed with 12 patients in the first stage. If at least one patient has pCR/RCB-1, 25 more patients will be added for a total of 37 patients (alpha = beta = 10%). This design has a 54% probability of early termination after the first stage if the true pCR or RCB-I probability is 5%. Contact information for people with a specific interest in the trial sdamodaran@mdanderson.org Citation Format: Senthil Damodaran, Jennifer K Litton, Kenneth R. Hess, Colleen T. Eppig, Krzysztof J. Grzegorzewski, Funda Meric-Bernstam, Ignacio I. Wistuba, Jason B White, Gaiane M. Rauch, Rosalind P. Candelaria, Beatriz E. Adrada, Bora Lim, Stacy L. Moulder, Debu Tripathy. A phase-2 trial of neoadjuvant alpelisib and nab-paclitaxel in anthracycline refractory triple negative breast cancers with PIK3CA or PTEN alterations [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr OT2-06-01.

Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC.To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) predict the response to NAST in TNBC.Prospective.A total of 108 patients with biopsy-proven TNBC who underwent NAST and definitive surgery during 2015-2020.A 3.0 T/rFOV single-shot diffusion-weighted echo-planar imaging sequence (DWI).Three scans were acquired longitudinally (pretreatment, after two cycles of NAST, and after four cycles of NAST). For each scan, 11 ADC histogram features (minimum, maximum, mean, median, standard deviation, kurtosis, skewness and 10th, 25th, 75th, and 90th percentiles) were extracted from tumors and from PTRs of 5 mm, 10 mm, 15 mm, and 20 mm in thickness with inclusion and exclusion of fat-dominant pixels.ADC features were tested for prediction of pCR, both individually using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC), and in combination in multivariable models with k-fold cross-validation. A P value 0.05 was considered statistically significant.Fifty-one patients (47%) had pCR. Maximum ADC from PTR, measured after two and four cycles of NAST, was significantly higher in pCR patients (2.8 ± 0.69 vs 3.5 ± 0.94 mmQuantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC.1 TECHNICAL EFFICACY: Stage 4.

Ishida, A, Travis, SK, Draper, G, White, JB, and Stone, MH. Player position affects relationship between internal and external training loads during Division I collegiate female soccer season. J Strength Cond Res 36(2): 513-517, 2022-The purpose of this study was to investigate how competition phase and player position affect the relationship between internal and external training loads (ITL and ETL, respectively) in collegiate female soccer. Seventeen players participated (21.8 ± 1.7 years; 165.1 ± 6.2 cm; and 63.7 ± 7.9 kg). Nineteen match-plays (10 nonconference and 9 conference) were completed during the 2019 competitive season, including 270 observations of 17 players (defenders = 5, midfielders = 9, and forwards = 3). Internal training load was assessed using session rating of perceived exertion (sRPE). External training load included total distance and high-speed running (HSR) distance. A linear mixed model was compiled with fixed effects of total distance, HSR, competition phase, and player position (defenders, midfielders, and forwards) and random effects of player. There were statistically significant main effects for total distance (p0.001), HSR (p = 0.047) and player position (p = 0.045) on the prediction model of sRPE. However, the main effect of competition phase did not statistically contribute to the prediction model of sRPE (p = 0.38). In the final model, total distance (p0.001) and player position for forwards (p = 0.008) were significant predictors of sRPE. However, there was no statistically significant fixed effect of HSR on sRPE (p = 0.15). The final model explained 60.6% of the variance in sRPE (R2 = 0.60), whereas the random effect also explained 6.1% of the variance (R2 = 0.06). Our findings indicated that total distance and player position were strong predictors of sRPE. The relationship between ITL and ETL should be monitored by player position in female soccer players.

Ishida, A, Suarez, DG, Travis, SK, Slaton, JA, White, JB, Bazyler, CD, and Stone, MH. Intrasession and intersession reliability of isometric squat, midthigh pull, and squat jump in resistance-trained individuals. J Strength Cond Res 37(1): 18-26, 2023-The purposes of this study were to investigate intrasession and intersession reliability of variables obtained from squat jump (SJ), shortened isometric midthigh pull (IMTP), and isometric squat (ISQ) protocols and to evaluate relationships between isometric and dynamic performance and 1 repetition maximum (1RM) back squat (BSQ). Eleven moderately resistance-trained men participated (27.8 ± 3.9 years; 175.0 ± 7.2 cm; 87.2 ± 11.4 kg). Subjects completed familiarization in the IMTP and ISQ, followed by 1RM BSQ at least 48 hours before the first performance test. Two performance tests occurred at 7-day intervals including SJ, IMTP, and ISQ. SJ variables included jump height (SJH), body mass (BM), peak force (PF), and peak power (PP). Isometric midthigh pull and ISQ variables included isometric peak force (IPF); relative IPF; rate of force development at 90, 200, and 250 milliseconds; and impulse at 90, 200, and 250 milliseconds. SJ, IMTP, and ISQ kinetic variables were considered reliable if intraclass correlations (ICCs) and coefficients of variations (CVs) were0.80 and10%. Intrasession and intersession reliability criteria were met for SJH, BM, PF, and PP (ICC = 0.91-1.00, CV = 0.5-9.1%). Isometric peak force and impulse at 200 and 250 milliseconds met intrasession and intersession reliability criteria for IMTP and ISQ (ICC = 0.90-0.99, CV = 2.1-8.1%). Significant large correlation was observed between 1RM BSQ and ISQ peak force (p = 0.038, r = 0.63), but not between 1RM BSQ and shortened IMTP peak force (p = 0.11, r = 0.50). Shortened IMTP and ISQ peak force and impulse are reliable kinetic variables, and ISQ peak force is indicative of 1RM BSQ in moderately resistance-trained men.

PURPOSE: To determine if amide proton transfer–weighted chemical exchange saturation transfer (APT(W) CEST) MRI is useful in the early assessment of treatment response in persons with triple-negative breast cancer (TNBC). MATERIALS AND METHODS: In this prospective study, a total of 51 participants (mean age, 51 years [range, 26–79 years]) with TNBC were included who underwent APT(W) CEST MRI with 0.9- and 2.0-µT saturation power performed at baseline, after two cycles (C2), and after four cycles (C4) of neoadjuvant systemic therapy (NAST). Imaging was performed between January 31, 2019, and November 11, 2019, and was a part of a clinical trial (registry number NCT02744053). CEST MR images were analyzed using two methods—magnetic transfer ratio asymmetry (MTR(asym)) and Lorentzian line shape fitting. The APT(W) CEST signals at baseline, C2, and C4 were compared for 51 participants to evaluate the saturation power levels and analysis methods. The APT(W) CEST signals and their changes during NAST were then compared for the 26 participants with pathology reports for treatment response assessment. RESULTS: A significant APT(W) CEST signal decrease was observed during NAST when acquisition at 0.9-µT saturation power was paired with Lorentzian line shape fitting analysis and when the acquisition at 2.0 µT was paired with MTR(asym) analysis. Using 0.9-µT saturation power and Lorentzian line shape fitting, the APT(W) CEST signal at C2 was significantly different from baseline in participants with pathologic complete response (pCR) (3.19% vs 2.43%; P = .03) but not with non-pCR (2.76% vs 2.50%; P > .05). The APT(W) CEST signal change was not significant between pCR and non-pCR at all time points. CONCLUSION: Quantitative APT(W) CEST MRI depended on optimizing acquisition saturation powers and analysis methods. APT(W) CEST MRI monitored treatment effects but did not differentiate participants with TNBC who had pCR from those with non-pCR. © RSNA, 2021 Clinical trial registration no. NCT02744053 Supplemental material is available for this article. Keywords Molecular Imaging-Cancer, Molecular Imaging-Clinical Translation, MR-Imaging, Breast, Technical Aspects, Tumor Response, Technology Assessment

Fields, JB, Merigan, JM, Gallo, S, White, JB, and Jones, MT. External and internal load measures during preseason training in men collegiate soccer athletes. J Strength Cond Res 35(9): 2572-2578, 2021-Collegiate athletes are exposed to high volume loads during preseason training. Monitoring training load can inform training and recovery periods. Therefore, the purpose was to examine changes in and bidirectional relationship between external and internal load metrics in men collegiate soccer athletes (n = 20; age, 20 ± 1 year). Internal load measures of heart rate variability (HRV), salivary testosterone (T) and cortisol (C), and self-assessment wellness and ratings of perceived exertion scales were collected daily. External load measures of total distance, player load, high-speed distance, high inertial movement analysis, and repeated high-intensity efforts were collected in each training session using global positioning system/global navigation satellite system technology. A 1-way analysis of variance determined weekly changes in external load, physiological, hormonal, and subjective self-assessment measures of internal load. Bidirectional prediction of external load markers and self-assessment measures on physiological and hormonal markers of internal load were assessed by hierarchical linear regression models (p < 0.05). External load measures, C, energy, sleep, and rate of perceived exertion (RPE) decreased (p < 0.01), whereas T, T:C ratio, anger, depression, and vigor increased (p < 0.01) from week 1 to week 2. Morning C positively predicted afternoon external load and post-training RPE (p < 0.05); T:C ratio negatively predicted afternoon external load and post-training RPE (p < 0.05); and morning HRV negatively predicted post-training RPE (p = 0.031). Despite reduced hormonal stress and external load across weeks, negative perceptions of fatigue increased, suggesting fatigue patterns may have a delayed response. Load may have a more belated, chronic effect on perceptions of fatigue, whereas hormonal changes may be more immediate and sensitive to change. Practitioners may wish to use a variety of external and internal load measures to understand athletes' stress responses to training.

The purpose of the study was to investigate the effects of using compound sets during a 12-week lower body resistance training program on muscle strength, endurance, hypertrophy, architecture, and soreness. Thirty-one recreationally active females were randomly assigned to one of three groups: traditional sets, compound sets, or control. The training groups performed Smith Machine squat and leg press at matched intensities, volumes, and cumulative rest per session. During compound sets, the squat was performed immediately prior to the leg press, while 1 min rest separated the exercises during traditional sets. A non-exercise control group did not perform resistance training. One-repetition maximum strength, muscle endurance, muscle thickness, cross-sectional area, pennation angle, training session time, and soreness were compared from pre- to post-training (α level 0.80), 24 (P > 0.50), or 48 (P > 0.30) h post-workout. In conclusion, compound set training, with equated rest, is a method of resistance training that elicits gains similar to traditional sets in young females.

BACKGROUND Dynamic contrast-enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response. PURPOSE To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). STUDY TYPE Prospective. POPULATION/SUBJECTS Sixty patients with biopsy-confirmed TNBC between December 2016 and September 2020. FIELD STRENGTH/SEQUENCE A 3.0 T/3D fast spoiled gradient echo-based DCE MRI ASSESSMENT: Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5-minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing. STATISTICAL TESTS Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann-Whitney U test. RESULTS About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non-pCR, with AUC (95% confidence interval [CI]) = 0.85 (0.74,0.95) (P

Triple-negative breast cancer (TNBC) accounts for 15–20% of breast cancer cases in the United States, lacks targeted therapeutic options, and is associated with a 40–80% risk of recurrence. Thus, identifying actionable targets in treatment-naïve and chemoresistant TNBC is a critical unmet medical need. To address this need, we performed high-throughput drug viability screens on human tumor cells isolated from 16 patient-derived xenograft models of treatment-naïve primary TNBC. The models span a range of TNBC subtypes and exhibit a diverse set of putative driver mutations, thus providing a unique patient-derived, molecularly annotated pharmacologic resource that is reflective of TNBC. We identified therapeutically actionable targets including kinesin spindle protein (KSP). The KSP inhibitor targets the mitotic spindle through mechanisms independent of microtubule stability and showed efficacy in models that were resistant to microtubule inhibitors used as part of the current standard of care for TNBC. We also observed subtype selectivity of Prima-1Met, which showed higher levels of efficacy in the mesenchymal subtype. Coupling pharmacologic data with genomic and transcriptomic information, we showed that Prima-1Met activity was independent of its canonical target, mutant p53, and was better associated with glutathione metabolism, providing an alternate molecularly defined biomarker for this drug.

PURPOSE: To investigate the value of performing mid-treatment axillary ultrasound (AUS) in triple-negative breast cancer (TNBC) patients who are undergoing neoadjuvant systemic therapy (NAST) by determining the optimal cutoff number of abnormal nodes associated with residual nodal disease on surgical pathology. MATERIALS AND METHODS: This sub-study, an interim analysis of an ongoing single-institution clinical trial enrolling patients with stage I-III TNBC, included 106 patients. Number of abnormal nodes at mid-treatment was assessed and recorded by experienced breast radiologists, who empirically categorized lymph nodes using a binary approach of sonographically-normal versus abnormal. Pathologic lymph node positivity was defined as presence of macrometastasis or micrometastasis in ≥1 axillary node from sentinel lymph node biopsy and/or axillary lymph node dissection. RESULTS: Of 106 patients, 26 (25 %) had residual nodal disease and 80 (75 %) had no nodal disease at surgery. Median number of abnormal nodes at mid-treatment was 5 (standard deviation [SD], 5) for patients with residual nodal disease and 0 (SD, 2) for patients with no nodal disease at surgery (p < 0.0001). TNBC patients with > 4 abnormal nodes at mid-treatment had a significantly higher chance of being node-positive at surgery (AUC = 0.908, p < 0.0001; PPV = 90 %). CONCLUSION: Our data suggest that a cutoff of > 4 abnormal nodes on mid-treatment AUS is associated with residual disease post-NAST. If our findings are substantiated by subsequent analyses, then mid-treatment AUS could be used to identify patients unlikely to achieve nodal pathologic complete response and who should be offered alternative therapy.

Monitoring internal load provides useful and non-invasive markers of training stress and adaptation. However, the relationship between internal load measures across a competitive window remains inconclusive and limited. The purpose of this study was to report various internal load measures, as well as their relationship, across a season in Division I women lacrosse athletes (n = 20). Ultra-short natural logarithm of the root mean square of successive differences (lnRMSSD), salivary testosterone, cortisol, the testosterone:cortisol ratio, and self-reported measures of fatigue and recovery were collected weekly for 13 weeks. Means ± SD were calculated to provide descriptive values and a repeated measure analysis of variance (ANOVA) was used to analyze changes in testosterone, cortisol, testosterone:cortisol ratio (n = 8), and lnRMSSD (n = 8) over the course of the season. Pearson correlations assessed relationships between all internal load measures. No significant time effect was observed in testosterone (p = 0.059), cortisol (p = 0.544), testosterone:cortisol ratio (p = 0.120), or lnRMSSD (p = 0.062). lnRMSSD was correlated with testosterone (r = 0.265), cortisol (r = −0.232), testosterone:cortisol ratio (r = 0.345), and fatigue (r = −0.256) (p < 0.05). More research is needed to examine relationships among markers of internal stress across all phases of the training cycle. Routine monitoring may help practitioners optimize training programming to reduce injury, illness, and overtraining.

Muscular strength is suggested to be dependent upon muscle characteristics. Yet, sex-specific relationships of muscle characteristics to strength in the resistance-trained require investigation. Therefore, the purpose was to evaluate sex differences in muscle characteristics and isometric strength in the elbow extensors, as well as their respective associations. Resistance-trained men (n = 15, mean ± SD 22 ± 4 years, 87.5 ± 12.8 kg, 16.9 ± 2.9% body fat) and women (n = 15, mean ± SD 25 ± 5 years, 59.3 ± 7.3 kg, 22.4 ± 4.2% body fat) were tested. B-mode ultrasound images assessed muscle thickness, pennation angle, and echo intensity. Muscle volume and fascicle length were estimated from previously validated equations. Maximal voluntary isometric contraction measured elbow extensors isometric strength. Independent samples t-tests and Fisher’s r-to-z test examined differences between sexes. Sex differences existed in all muscle characteristics (p

Background and Purpose:There is currently a lack of recognized imaging criteria for prediction of treatment response to NAST in breast cancer patients with recent reports showing that breast MRI is the most accurate modality for evaluation of NAST response. DCE-MRI evaluates tumor perfusion that influences tumor enhancement at the post-contrast subtraction images and allows for more accurate measurement of changes in tumor volume during NAST. In this study, we evaluated the ability of tumor volumetric changes after 2 and 4 cycles of NAST by longitudinal ultrafast DCE-MRI to predict pathologic complete response (pCR) in TNBC undergoing NAST. Materials and Methods: Stage I-III TNBC patients enrolled in an IRB approved prospective clinical trial (ARTEMIS, NCT02276433) who had ultrafast DCE-MRI at baseline (BL, N=103), post 2 cycles (C2, N=59), and post 4 cycles (C4, N=103) of anthracycline-based NAST,and had surgery, were included in this analysis. Tumor volume was calculated using 3D measurements of the index lesion at BL, C2, and C4. Percent change of tumor volume (%TV) between BL, C2, and C4 was calculated at early (9-12 sec) and delayed (360-480 sec) phases of DCE-MRI. The largest lesion was used for analysis in patients with multicentric or multifocal disease. Demographic, clinical, and pathologic data and treatment response at surgery (pCR versus non-pCR) were documented. Receiver operating characteristics curve (ROC) analysis was performed for prediction of pCR status. Positive predictive value (PPV), negative predictive value (NPV) and Youden Index were used to select %TV cut-off thresholds for pCR prediction.Results: 103 patients (median age, 53 years; range, 24-79 years) were included, 48 (47%) had pCR, and 55 (53%) had non-pCR at surgical pathology. The %TV reduction at C2 DCE-MRI was predictive of pCR on both early phase DCE MRI (AUC, 0.873; CI:0.779-0.968, p < .0001) and delayed phase DCE MRI (AUC, 0.844; CI:0.742-0.947, p < .0001). Optimal thresholds were as follows: 70% TV reduction on early phase DCE MRI with Youden’s index of 1.58 was able to predict pCR correctly for 79% of patients with PPV of 81%; 75% TV reduction on delayed phase with Youden’s Index of 1.44 was able to predict pCR correctly for 71% of patients with PPV of 85%.%TV reduction was also predictive of pCR at the C4 time point on both early phase DCE MRI (AUC, 0.761; CI:0.665-0.856, p < .0001) and delayed phase DCE MRI (AUC, 0.737; CI:0.641-0.833, p < .0001). Optimal thresholds were as follows: 90% TV reduction on early phase DCE MRI with Youden’s index of 1.43 was able to correctly predict pCR in 72% of patients with PPV of 70%; and 90% TV reduction on delayed phase with Youden’s Index of 1.34 was able to predict pCR correctly in 68% of patients with PPV of 71%.Conclusion: Our data shows that percent tumor volume reduction by DCE-MRI after 2 and 4 cycles of NAST was able to predict pCR in TNBC with high accuracy and can be used as an early imaging biomarker of NAST response prediction. Volumetric changes by longitudinal DCE-MRI can be used to differentiate chemoresistant and chemosensitive TNBC patients as early as after 2 cycles of NAST, and can help to triage patients for treatment de-escalation or targeted therapy. Citation Format: Gaiane Margishvili Rauch, Adrada E Beatriz, Rosalind P Candelaria, Nabil Elshafeey, Abeer H Abdelhafez, Benjamin C Musall, Jia Sun, Medina Boge, Rania M.M Mohamed, Jong Bum Son, Shu Zhang, Jessica Leung, Deanna Lane, Marion Scoggins, David Spak, Elsa Arribas, Lumarie Santiago, Gary J Whitman, Huong T. Le-Petross, Tanya W Moseley, Jason B. White, Elizabeth Ravenberg, Ken-Pin Hwang, Peng Wei, Lei Huo, Jennifer K Litton, Vicente Valero, Debu Tripathy, Alastair M Thompson, Mark D Pagel, Jingfei Ma, Wei T Yang, Stacy Moulder. Volumetric changes on longitudinal dynamic contrast enhanced MR imaging (DCE-MRI) as an early treatment response predictor to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD6-07.